Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 191–200 of 4856 papers

Title	Date	Tasks	Status	Hype
AGATE: Stealthy Black-box Watermarking for Multimodal Model Copyright Protection	Apr 28, 2025	Adversarial AttackAnomaly Detection	—Unverified	0
Reservoir-enhanced Segment Anything Model for Subsurface Diagnosis	Apr 26, 2025	Anomaly DetectionGPR	CodeCode Available	5
Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics	Apr 26, 2025	Anomaly DetectionImputation	—Unverified	0
Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications	Apr 26, 2025	Active LearningAnomaly Detection	CodeCode Available	0
Time and Frequency Domain-based Anomaly Detection in Smart Meter Data for Distribution Network Studies	Apr 25, 2025	Anomaly Detection	—Unverified	0
Statistical Inference for Clustering-based Anomaly Detection	Apr 25, 2025	Anomaly DetectionClustering	—Unverified	0
Fault Diagnosis in New Wind Turbines using Knowledge from Existing Turbines by Generative Domain Adaptation	Apr 24, 2025	Anomaly DetectionDomain Adaptation	—Unverified	0
Quantum Autoencoder for Multivariate Time Series Anomaly Detection	Apr 24, 2025	Anomaly DetectionData Compression	—Unverified	0
Unsupervised Time-Series Signal Analysis with Autoencoders and Vision Transformers: A Review of Architectures and Applications	Apr 23, 2025	Anomaly DetectionDomain Generalization	—Unverified	0
Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models	Apr 22, 2025	Anomaly DetectionComputational Efficiency	—Unverified	0

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All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified